Tag Archives: NIRS

This is part 2 of a series (part 1 is here) on trying to study near-infrared spectroscopy in the prehospital setting by Dr Andrew Weatherall (@AndyDW_). Can NIRS work? No one can be sure but here’s one approach to getting some data we can actually use.

A while back I did a post where I pointed out that when you get sold technology, there’s a whole history behind the machine that goes beep that means it’s probably not what you’re told. And the example I used was near-infrared spectroscopy tissue oximetry.

That was partly because I’m involved in research on NIRS monitoring and I’ve spent a lot of time looking at it. Like every time I look carefully in the mirror, there’s a lot of blemishes that I miss on a casual glance. I also don’t mind pointing out those blemishes.

So that post was about all the things that could get in the way – light bouncing about like a pinball, humans being distressingly uncatlike, comparing monitors that are might be apples and aardvarks rather than apples and apples and basing your whole methodology on assumptions of tissue blood compartments. Oh, and maybe you can’t get sunlight near your red light.

Sheesh.

The thing is, I really want to answer that original question – “How’s the brain?”

So enough of the problems, can we find some solutions?

Actually I’m not certain. But I can say what we came up with. It’s a plan that involves sandpits, hiding numbers and finding better eyes. Oh, and changing the design of monitors forever and ever.

Playing in Sandpits

Our first step was to try and figure out if NIRS technology could even work in the places it wasn’t designed for. Not near the cosy bleeping of an operating theatre monitor where the roughest conditions might be inflicted by a rogue playlist.

We figured that the first issues might be all the practical things that stop monitors working so effectively. And we already knew that in the operating suite you often needed to provide shielding from external light to allow reliable measurements.

So we asked for volunteers, stuck sensors to their heads and took them driving in an ambulance or hopped on the helicopter to do some loops near Parramatta. It gave us lots of chances to figure out the practicalities of using an extra monitor too.

And we learnt a bit. That we could do it with some layers of shielding between the sensors and the outside world. That the device we tested, though comfortable next to an intensive care bed was a bit unwieldy at 6 kg and 30 cm long to be carried to the roadside. Most importantly that it was worth pushing on, rather than flattening everything in the sandpit and starting again.

Early engineering advice included “just put a tinfoil hat on everyone to shield the sensors”. I just … I … can’t … [via eclipse_etc at Flickr ‘The Commons’]

Hiding Numbers and Getting Out of the Way

The next thing that was pretty obvious was that we couldn’t set out to figure out what NIRS monitoring values were significant and at the same time deliver treatments on the basis of those numbers. We needed to prospectively look at the data from the monitor and see what associations were evident and establish which bits in the monitoring actually mattered for patients and clinicians.

Of course paramedics and doctors tend to like to fix stuff. Give them a “regional saturation” number which looks a little like mixed venous oxygen saturation while the manufacturer (usually) puts a little line on the screen as the “good-bad” cutoff line is a pretty good way to see that fixing reflex kick in. So to make sure it really is a prospective observational study and we’re observing what happens in actual patients receiving their usual treatment we ended up with a monitor with none of the numbers displayed. Better not to be tempted.

It was also obvious that we couldn’t ask the treating team to look after the NIRS monitor because they’d immediately stop doing the same care they always do and occasionally (or always) they’ll be distracted by the patient from being as obsessive about the NIRS monitor as we need for research.

So recruiting needs a separate person just to manage the monitor. On the plus side this also means we can mark the electronic record accurately when treatments like anaesthesia, intubation and ventilation or transfusion happen (or indeed when the patient’s condition obviously changes). It’s all more data that might be useful.

Getting Better Eyes

One of the big problems with NIRS tissue oximetry so far seems to be that the “absolute oximetry” isn’t that absolute. When you see something claiming a specific number is the cutoff where things are all good or bad, you can throw a bucket of salt on that, not just a pinch.

Maybe all of this salt. [via user pee vee at Flickr’s ‘The Commons’]The other thing is that to pick up evolving changes in a dynamic clinical environment is difficult. What if it isn’t just the change in oximetry number, but the rate of change that matters? What if it’s the rate of change in that number vs the change over the same time in total haemoglobin measurements, or balance between cerebral monitoring and peripheral monitoring at the same time? How does a clinician keep track of that?

What we might need is a way of analysing the information that looks for patterns in the biological signals or can look at trends. The good news is there’s people who can do that as it’s acutally a pretty common thing for clever biomedical engineers to consider. So there are some clever biomedical engineers who will be part of looking at the data we obtain. When they have spare time from building a bionic eye.

My bet is that if NIRS monitoring is ever to show real benefits to patients it won’t be only by looking at regional saturation (though we’ll try that too). It will be the way we look at the data that matters. Examining rapidly changing trends across different values might just be the key.

Thinking About the Monitors We Need

Let’s imagine it all works. Let’s assume that even with all those hurdles the analysis reveals ways to pretty reliably pick up haematomas are developing, or the brain is not receiving enough blood flow, or oedema is developing (and there are other settings where these things have been shown), there’s still a big problem. How do you make that information useful to a clinician who has a significant cognitive load while looking after a patient?

For each NIRS sensor that is on (3 in this study) we’ll be generating 4 measurements with trendlines. The patient is likely to have pulse oximetry, ECG, blood pressure and often end-tidal capnography too. Putting together multiple bits of information is an underappreciated skill that highly trained clinicians make a part of every day. But it adds a lot of work. How would you go with 12 more monitoring values on the screen?

Yes Sclater’s lemur, that’s 16 monitoring values to keep track of. [via user Tambako the Jaguar at flickr]So before we can take any useful stuff the analysis reveals and free clinicians to use the information, we need to figure out how to present it in a way that lets them glance at the monitor and understand it.

How should we do that? Well it’s a bit hard to know until we know what we need to display. My current guess is that it will involve getting clever graphics people to come up with a way to display the aggregated information through shapes and colours rather than our more familiar waveforms (and that’s not an entirely novel idea, other people have been on this for a bit).

So then we’d need to test the most effective way to show it before finally trying interventional studies.

This could take a bit.

And that is a story about the many, many steps for just one group trying to figure out if a particular monitor might work in the real world of prehospital medicine. There are others taking steps on their own path with similar goals and I’m sure they’ll all do it slightly differently.

I hope we end up bumping into each other somewhere along the road.

Notes and References:

Here’s the link to our first volunteer study (unfortunately Acta Anaesthesiologica Scandinavica has a paywall):

This weeks post is the first in a series touching on some of the challenges when you start researching technology for the prehospital setting (or anywhere really). Dr Andrew Weatherall (@AndyDW_) on why some monitors aren’t the monitors you’re sold.

I am new to the research game. As is often the case, that brings with it plenty of zeal and some very rapid learning. When we first started talking about the project that’s now my PhD, we set out wondering if we could show something that was both a bit new and a positive thing to add to patient clinical care.

It didn’t take long to realise we’d still be doing something worthwhile if the project didn’t work one little bit.

Yep, if this thing doesn’t work, that would still be fine.

Simple Questions

I’m going to assume no one knows anything about this project (seems the most realistic possibility). It’s a project about brains and lights and monitors.

It came out of two separate areas of work. One of these was the prehospital bit of my practice. All too often I’d be at an accident scene, with an unconscious patient and irritated by the big fuzzy mess at the middle of the clinical puzzle.

“How’s the brain?”

Not “how are the peripheral readings of saturation and blood pressure against the normative bell curve?” Not “how are the gross clinical neurological signs that will change mostly when things get really grim?”

“How’s the brain?”

At the same time at the kids’ hospital where I do most of my anaesthesia we were introducing near-infrared spectroscopy tissue oximetry to monitor the brain, particularly in cardiac surgery cases.

The story sounded good. A noninvasive monitor, not relying on pulsatile flow, that provides a measure of oxygen levels in the tissue where you place the probe (referred to as regional oxygen saturation, or tissue saturation or some other variant and turned in to the ideal number on a scale between 0 and 100) and which reacts quickly to any changes. You can test it out by putting a tourniquet on your arm and watching the magic oxygen number dive while you inflate it.

Except of course it’s not really as simple as that. If you ask a rep trying to sell one of these non-invasive reflectance spectroscopy (NIRS) devices, they’ll dazzle you with all sorts of things that are a bit true. They’re more accurate now. They use more wavelengths now. Lower numbers in the brain are associated with things on scans.

But it’s still not that simple. Maybe if I expand on why that is, it will be clearer why I say I would be OK with showing it doesn’t work. And along the way, there’s a few things that are pertinent when considering the claims of any new monitoring systems.

A Bit About Tech

Back in 1977, a researcher by the name of Franz Jöbsis described a technique where you could shine light through brain tissue, look at the light that made it out the other side and figure out stuff about the levels of oxygen and metabolism happening deep in that brain tissue. This was the start of tissue spectroscopy.

Now, it’s 38 years later and this technology isn’t standard. We’re still trying to figure out what the hell to do with it. That might just be the first clue that it’s a bit complicated.

Of course the marketing will mention it’s taken a while to figure it out. Sometimes they’ll refer to the clinical monitors of the 1990’s and early 2000’s and mention it’s got better just recently. They don’t really give you the full breadth of all the challenges they’ve dealt with along the way. So why not look at just a few?

Humans Aren’t Much Like Cats

Jöbsis originally tested his technique on cats. And while you might find it hard to convince cat lovers, the brain of a cat isn’t that close to a human’s, at least in size. (As an aside, I’m told by clever bionic eye researchers the cat visual cortex actually has lots of similarities with that of humans – not sure that explains why the aquarium is strangely mesmerising though).

He also described it as a technique where you shone the light all the way across the head and picked up the transmitted light on the other side. But even the most absent-minded of us has quite a bit more cortex to get through than our feline friends and you’d never pick up anything trying that in anything but a neonate.

So the solution in humans has been to send out near-infrared light and then detect the amount that returns to a detector at the skin, on the same side of the head as you initially shone those photons.

When you get handed a brochure by a rep for one of these devices, they’ll show a magical beam of light heading out into the tissues and tracing a graceful arc through the tissues and returning to be picked up. You are given to believe it’s an orderly process, and that every bit of lost light intensity has been absorbed by helpful chromophores. In that case that would be oxy- and deoxyhaemoglobin, cytochromes in the cell and pesky old melanin if you get too much hair in the way.

See? Here’s the pretty version that comes with the monitor we’re using in the study? [It’s the Nonin EQUANOX and we bought it outright.]Except that’s the version of the picture where they’ve put Vaseline on the lens. Each one of those photons bounces eratically all over the place. It’s more like a small flying insect with the bug equivalent of ADHD bouncing around the room and eventually finding its way back to the window it flew in.

So when you try to perform the underlying calculations for what that reduction in light intensity you detect means, you need to come up with a very particular means of trying to allow for all that extra distance the photons travel. Then you need to average the different paths of all those photons not just the one photon. Then you need to allow for all the scattering that means some of the light will never come back your way.

That’s some of those decades of development chewed up right there.

Everyone Looks the Same But They Are Different

So that explains the delay then. Well there’s another thing that might make it hard to apply the technology in the prehospital environment. Every machine is different. Yep. If you go between systems, it’s might just be that you’re not comparing apples with apples.

That particular challenge of calculating the distance the light travels? Every manufacturer pretty much has a different method for doing it. And they won’t tell you how they do it (with the notable exception of the team that makes the NIRO device who have their algorithms as open access – and their device weighs 6 kg and is as elegant to carry as a grumpy baby walrus).

So when you read a paper describing the findings with any one device, you can’t be 100% sure it will match another device. This is some of the reason that each company calls their version of the magic oxygen number something slightly different from their competitor (regional saturation, tissue oxygenation index, absolute tissue oxygen saturation just to name a few). It might be similar, but it’s hard to be sure.

Maybe that’s harsh. Could a walrus be anything but elegant? [via Allan Hopkins on flickr without mods under CC 2.0]

When “Absolute” Absolutely Isn’t Absolute

You get your magic number (I’m going to keep calling it regional saturation for simplicity) and it’s somewhere between 60 and 75% in the normal person. The thing is it hasn’t been directly correlated with a gold standard real world measurement that correlates with the same area sampled.

The NIRS oximeter makes assumptions about the proportions of arterial, venous and capillary blood in the tissue that’s there. The regional saturations are validated against an approximation via other measures, like jugular venous saturation or direct tissue oximetry.

On top of that all those “absolute NIRS monitors” that give you a definite number that means something? No. “Absolute” is not a thing.

It’s true the monitors have got much better in responding to changes quickly. And they’ve added more wavelengths and are based on more testing so they are more accurate than monitors from decades past. But they can still have significant variation in their readings (anywhere up to 10% is described).

And they spit out a number, regional saturation, that is actually an attempt to take lots of parameters and spit out a number a clinician can use. How many parameters? Check the photo.

This is from an excellent review by Elwell and Cooper. [Elwell CE, Cooper CE. Making light work: illuminating the future of biomedical optics. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2011;369:4358-4379.]

The Practical bits

And after all that, we reach the practical issues. Will sunlight contaminate the sample? Can it cope with movement? Do you need a baseline measurement first? Does it matter that we can only really sample the forehead in our setting?

All the joy of uncertainty before you even try to start to research.

So why bother?

Well the quick answer is that it might be better for patients for clinicians to actually know what is happening to the tissue in the brain. And acknowledging challenges doesn’t mean that it isn’t worth seeing if it’s still useful despite the compromises you have to make to take the basic spectroscopy technique to the clinical environment.

But even if we find it just doesn’t tell us useful stuff, we could at least provide some real world information to counter the glossy advertising brochure.

There are already people saying things like,

“You can pick up haematomas.” (In a device that just tells you if there’s a difference between the two hemispheres.)

“Low regional saturations are associated with worse outcomes.” (But that’s probably been demonstrated more in particular surgical settings and the monitoring hasn’t been shown to improve patient outcomes yet.)

“You can even pick up cytochromes.” (In the research setting in a specially set-up system that are way more accurate than any clinical devices.)

All of those statements are a bit true, but not quite the whole story. The other message I extract from all of this is that all this uncertainty in the detail behind the monitor can’t be unique to NIRS oximetry. I have little doubt it’s similar for most of the newer modalities being pushed by companies. Peripherally derived Hb measurements from your pulse oximeter sound familiar?

After all this it’s still true that if we can study NIRS oximetry in the environment that matters to us we might get an exciting new answer. Or we might not. And sometimes,

“Yeah … nah.”

Is still an answer that’s pretty useful.

This is the first in a series. The next time around, I’ll chat about the things we’re trying in the design of the study to overcome some of these challenges.

If you made it this far and want to read a bit more about the NIRS project, you can check out the blog I set up ages ago that’s more related to that (though it frequently diverts to other stuff). It’s here.